59 citations · 130 across the 11 of their papers we have counts for
12 papers
Data-driven stabilization of nonlinear systems via descriptor embedding
Mohammad Alsalti, Claudio De Persis, Victor G. Lopez +1
We introduce the notion of descriptor embedding for nonlinear systems and use it for the data-driven design of stabilizing controllers. Specifically, we provide sufficient data-dep…
Robust and efficient data-driven predictive control
Mohammad Alsalti, Manuel Barkey, Victor G. Lopez +1
We propose a robust and efficient data-driven predictive control (eDDPC) scheme which is more sample efficient (requires less offline data) compared to existing schemes, and is als…
An efficient data-based off-policy Q-learning algorithm for optimal output feedback control of linear systems
Mohammad Alsalti, Victor G. Lopez, Matthias A. Müller
In this paper, we present a Q-learning algorithm to solve the optimal output regulation problem for discrete-time LTI systems. This off-policy algorithm only relies on using persis…
Notes on data-driven output-feedback control of linear MIMO systems
Mohammad Alsalti, Victor G. Lopez, Matthias A. Müller
Recent works have approached the data-driven design of dynamic output-feedback controllers for discrete-time LTI systems by constructing non-minimal state vectors composed of past…
Sample- and computationally efficient data-driven predictive control
Mohammad Alsalti, Manuel Barkey, Victor G. Lopez +1
Recently proposed data-driven predictive control schemes for LTI systems use non-parametric representations based on the image of a Hankel matrix of previously collected, persisten…
Data-based system representations from irregularly measured data
Mohammad Alsalti, Ivan Markovsky, Victor G. Lopez +1
Non-parametric representations of dynamical systems based on the image of a Hankel matrix of data are extensively used for data-driven control. However, if samples of data are miss…
On the design of persistently exciting inputs for data-driven control of linear and nonlinear systems
Mohammad Alsalti, Victor G. Lopez, Matthias A. Müller
In the context of data-driven control, persistence of excitation (PE) of an input sequence is defined in terms of a rank condition on the Hankel matrix of the input data. For nonli…
Data-driven Nonlinear Predictive Control for Feedback Linearizable Systems
Mohammad Alsalti, Victor G. Lopez, Julian Berberich +2
We present a data-driven nonlinear predictive control approach for the class of discrete-time multi-input multi-output feedback linearizable nonlinear systems. The scheme uses a no…
Practical exponential stability of a robust data-driven nonlinear predictive control scheme
Mohammad Alsalti, Victor G. Lopez, Julian Berberich +2
We provide theoretical guarantees for recursive feasibility and practical exponential stability of the closed-loop system of a feedback linearizable nonlinear system when controlle…
Data-based Control of Feedback Linearizable Systems
Mohammad Alsalti, Victor G. Lopez, Julian Berberich +2
We present an extension of Willems' Fundamental Lemma to the class of multi-input multi-output discrete-time feedback linearizable nonlinear systems, thus providing a data-based re…
Efficient Off-Policy Q-Learning for Data-Based Discrete-Time LQR Problems
Victor G. Lopez, Mohammad Alsalti, Matthias A. Müller
This paper introduces and analyzes an improved Q-learning algorithm for discrete-time linear time-invariant systems. The proposed method does not require any knowledge of the syste…
Data-Based System Analysis and Control of Flat Nonlinear Systems
Mohammad Alsalti, Julian Berberich, Victor G. Lopez +2
Willems et al. showed that all input-output trajectories of a discrete-time linear time-invariant system can be obtained using linear combinations of time shifts of a single, persi…